A New Network Security Evaluation Model Based on Multi-Data and Layer

Abstract:

The last few years, research on network risk evaluation technique[1], and establishment of risk evaluation system facing integrity grade protection is the hot problem. There is great significance. The existing network safety valuation system exists many blemishes in science, and nationality, etc. Such as pole light, Nessus, Anluo network risk valuation system etc, they evaluate only from loophole scan or permeating test etc. There Lack important contents, for example, the safe grade and safety of target management strategy of the evaluation network. The standards, such as CC and OB 17859, OBIT 18336, OBIT 20984[2] etc ,are the outline requests , don't have easy operability. The existing network safety valuation methods and models, for example, network safety valuation model based on the discharge attack judges[3] , visit control model[4], network safety valuation model based on the diagram talks[5], all have blemish, there have a few evaluate objects, it's strong to limit, the function is bad. To resolve the above problem, this paper provides a model named NSEMML (Network Security Evaluation Model based on Multi-data and Layer), And a new risk evaluation system based on FNSEM is developed.

• Periodical: Key Engineering Materials (Volumes 474-476)
• Pages: 1440-1446
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.474-476.1440
• Online since: April 2011
• Authors: Xiao Hu Ma
• Keywords: Evaluation System, FNSEM, Network Security Evaluation

References

[1] SpanglerR. Analysis of Remote Active Operating System Fingerprinting Tools [Z]. University of Wisconsin, 2006, 34(05) 25-30.

[2] GB/T 20984-2007. Information security technology information safety risk assessment standard[S]. China's national quality supervision, inspection and quarantine2007.

[3] Yi Wang, HanPing Hu, ZuXi Wang etc. Based on trafc safety evaluation of network attack model[J]. Huazhong university of science and technology joural (natural science edition). 2008, 36(4): 37-40.

[4] Pyfe C, Jain L. Teams of intelligent agents which lear using artifcial immune systems [J]. Joural of Network and Com-puter Applications, 2006, 29(3) 147-159.

[5] YongJie Wang, Ming Xian, Jing Liu, etc. Based on the network attack graph model of safety evaluation[J]. Joural of communication, 2007, 28(3) 29-34.